{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "path = os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 284807 entries, 0 to 284806\n",
      "Data columns (total 31 columns):\n",
      "Time      284807 non-null float64\n",
      "V1        284807 non-null float64\n",
      "V2        284807 non-null float64\n",
      "V3        284807 non-null float64\n",
      "V4        284807 non-null float64\n",
      "V5        284807 non-null float64\n",
      "V6        284807 non-null float64\n",
      "V7        284807 non-null float64\n",
      "V8        284807 non-null float64\n",
      "V9        284807 non-null float64\n",
      "V10       284807 non-null float64\n",
      "V11       284807 non-null float64\n",
      "V12       284807 non-null float64\n",
      "V13       284807 non-null float64\n",
      "V14       284807 non-null float64\n",
      "V15       284807 non-null float64\n",
      "V16       284807 non-null float64\n",
      "V17       284807 non-null float64\n",
      "V18       284807 non-null float64\n",
      "V19       284807 non-null float64\n",
      "V20       284807 non-null float64\n",
      "V21       284807 non-null float64\n",
      "V22       284807 non-null float64\n",
      "V23       284807 non-null float64\n",
      "V24       284807 non-null float64\n",
      "V25       284807 non-null float64\n",
      "V26       284807 non-null float64\n",
      "V27       284807 non-null float64\n",
      "V28       284807 non-null float64\n",
      "Amount    284807 non-null float64\n",
      "Class     284807 non-null int64\n",
      "dtypes: float64(30), int64(1)\n",
      "memory usage: 67.4 MB\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv(path + '/creditcard.csv')\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.359807</td>\n",
       "      <td>-0.072781</td>\n",
       "      <td>2.536347</td>\n",
       "      <td>1.378155</td>\n",
       "      <td>-0.338321</td>\n",
       "      <td>0.462388</td>\n",
       "      <td>0.239599</td>\n",
       "      <td>0.098698</td>\n",
       "      <td>0.363787</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018307</td>\n",
       "      <td>0.277838</td>\n",
       "      <td>-0.110474</td>\n",
       "      <td>0.066928</td>\n",
       "      <td>0.128539</td>\n",
       "      <td>-0.189115</td>\n",
       "      <td>0.133558</td>\n",
       "      <td>-0.021053</td>\n",
       "      <td>149.62</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.191857</td>\n",
       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
       "      <td>0.448154</td>\n",
       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
       "      <td>-0.078803</td>\n",
       "      <td>0.085102</td>\n",
       "      <td>-0.255425</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.225775</td>\n",
       "      <td>-0.638672</td>\n",
       "      <td>0.101288</td>\n",
       "      <td>-0.339846</td>\n",
       "      <td>0.167170</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.358354</td>\n",
       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "      <td>378.66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.966272</td>\n",
       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "      <td>123.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
       "      <td>0.403034</td>\n",
       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009431</td>\n",
       "      <td>0.798278</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>0.141267</td>\n",
       "      <td>-0.206010</td>\n",
       "      <td>0.502292</td>\n",
       "      <td>0.219422</td>\n",
       "      <td>0.215153</td>\n",
       "      <td>69.99</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...         V21       V22       V23       V24  \\\n",
       "0  0.098698  0.363787  ...   -0.018307  0.277838 -0.110474  0.066928   \n",
       "1  0.085102 -0.255425  ...   -0.225775 -0.638672  0.101288 -0.339846   \n",
       "2  0.247676 -1.514654  ...    0.247998  0.771679  0.909412 -0.689281   \n",
       "3  0.377436 -1.387024  ...   -0.108300  0.005274 -0.190321 -1.175575   \n",
       "4 -0.270533  0.817739  ...   -0.009431  0.798278 -0.137458  0.141267   \n",
       "\n",
       "        V25       V26       V27       V28  Amount  Class  \n",
       "0  0.128539 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.167170  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.327642 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3  0.647376 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4 -0.206010  0.502292  0.219422  0.215153   69.99      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 数据探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = list(data.columns)\n",
    "features[0] = 'Class'\n",
    "features[-1] = 'Time'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1 各特征与类别标签间的统计关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入统计分析模块\n",
    "from scipy import stats\n",
    "\n",
    "# 察看各变量间的P值与拟合情况\n",
    "statistic = []\n",
    "for i in range(len(features) - 1):\n",
    "    for j in range(i + 1, len(features)):\n",
    "        stat = []\n",
    "        # 计算两变量间的相关系数、P值\n",
    "        r, p = stats.pearsonr(data[features[i]], data[features[j]])\n",
    "        stat.append(features[i])\n",
    "        stat.append(features[j])\n",
    "        stat.append(r)\n",
    "        stat.append(p)\n",
    "        statistic.append(stat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_stats = pd.DataFrame(statistic,\n",
    "                             columns = ['FEATURE_X',\n",
    "                                        'FEATURE_Y',\n",
    "                                        'PERSON_R',\n",
    "                                        'P']\n",
    "                            )\n",
    "del statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FEATURE_X</th>\n",
       "      <th>FEATURE_Y</th>\n",
       "      <th>PERSON_R</th>\n",
       "      <th>P</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Class</td>\n",
       "      <td>V1</td>\n",
       "      <td>-1.013473e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Class</td>\n",
       "      <td>V2</td>\n",
       "      <td>9.128865e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Class</td>\n",
       "      <td>V3</td>\n",
       "      <td>-1.929608e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Class</td>\n",
       "      <td>V4</td>\n",
       "      <td>1.334475e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Class</td>\n",
       "      <td>V5</td>\n",
       "      <td>-9.497430e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Class</td>\n",
       "      <td>V6</td>\n",
       "      <td>-4.364316e-02</td>\n",
       "      <td>4.213111e-120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Class</td>\n",
       "      <td>V7</td>\n",
       "      <td>-1.872566e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Class</td>\n",
       "      <td>V8</td>\n",
       "      <td>1.987512e-02</td>\n",
       "      <td>2.740673e-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Class</td>\n",
       "      <td>V9</td>\n",
       "      <td>-9.773269e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Class</td>\n",
       "      <td>V10</td>\n",
       "      <td>-2.168829e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Class</td>\n",
       "      <td>V11</td>\n",
       "      <td>1.548756e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Class</td>\n",
       "      <td>V12</td>\n",
       "      <td>-2.605929e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Class</td>\n",
       "      <td>V13</td>\n",
       "      <td>-4.569779e-03</td>\n",
       "      <td>1.473734e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Class</td>\n",
       "      <td>V14</td>\n",
       "      <td>-3.025437e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Class</td>\n",
       "      <td>V15</td>\n",
       "      <td>-4.223402e-03</td>\n",
       "      <td>2.420143e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Class</td>\n",
       "      <td>V16</td>\n",
       "      <td>-1.965389e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Class</td>\n",
       "      <td>V17</td>\n",
       "      <td>-3.264811e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Class</td>\n",
       "      <td>V18</td>\n",
       "      <td>-1.114853e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Class</td>\n",
       "      <td>V19</td>\n",
       "      <td>3.478301e-02</td>\n",
       "      <td>5.801517e-77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Class</td>\n",
       "      <td>V20</td>\n",
       "      <td>2.009032e-02</td>\n",
       "      <td>7.964292e-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Class</td>\n",
       "      <td>V21</td>\n",
       "      <td>4.041338e-02</td>\n",
       "      <td>3.002269e-103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Class</td>\n",
       "      <td>V22</td>\n",
       "      <td>8.053175e-04</td>\n",
       "      <td>6.673597e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Class</td>\n",
       "      <td>V23</td>\n",
       "      <td>-2.685156e-03</td>\n",
       "      <td>1.518602e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Class</td>\n",
       "      <td>V24</td>\n",
       "      <td>-7.220907e-03</td>\n",
       "      <td>1.163760e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Class</td>\n",
       "      <td>V25</td>\n",
       "      <td>3.307706e-03</td>\n",
       "      <td>7.752501e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Class</td>\n",
       "      <td>V26</td>\n",
       "      <td>4.455398e-03</td>\n",
       "      <td>1.741971e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Class</td>\n",
       "      <td>V27</td>\n",
       "      <td>1.757973e-02</td>\n",
       "      <td>6.441920e-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Class</td>\n",
       "      <td>V28</td>\n",
       "      <td>9.536041e-03</td>\n",
       "      <td>3.595354e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Class</td>\n",
       "      <td>Amount</td>\n",
       "      <td>5.631753e-03</td>\n",
       "      <td>2.651221e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Class</td>\n",
       "      <td>Time</td>\n",
       "      <td>-1.232257e-02</td>\n",
       "      <td>4.818269e-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>V22</td>\n",
       "      <td>Amount</td>\n",
       "      <td>-6.480065e-02</td>\n",
       "      <td>1.326596e-262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>V22</td>\n",
       "      <td>Time</td>\n",
       "      <td>1.440591e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>V23</td>\n",
       "      <td>V24</td>\n",
       "      <td>6.721881e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>V23</td>\n",
       "      <td>V25</td>\n",
       "      <td>-7.216610e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>V23</td>\n",
       "      <td>V26</td>\n",
       "      <td>1.284235e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>V23</td>\n",
       "      <td>V27</td>\n",
       "      <td>4.382861e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>V23</td>\n",
       "      <td>V28</td>\n",
       "      <td>1.364554e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>V23</td>\n",
       "      <td>Amount</td>\n",
       "      <td>-1.126326e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>V23</td>\n",
       "      <td>Time</td>\n",
       "      <td>5.114236e-02</td>\n",
       "      <td>3.134910e-164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>V24</td>\n",
       "      <td>V25</td>\n",
       "      <td>1.241447e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>V24</td>\n",
       "      <td>V26</td>\n",
       "      <td>1.875868e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>V24</td>\n",
       "      <td>V27</td>\n",
       "      <td>-3.054513e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>V24</td>\n",
       "      <td>V28</td>\n",
       "      <td>-2.789797e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>V24</td>\n",
       "      <td>Amount</td>\n",
       "      <td>5.146217e-03</td>\n",
       "      <td>6.025251e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>V24</td>\n",
       "      <td>Time</td>\n",
       "      <td>-1.618187e-02</td>\n",
       "      <td>5.803460e-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>V25</td>\n",
       "      <td>V26</td>\n",
       "      <td>2.435139e-15</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>V25</td>\n",
       "      <td>V27</td>\n",
       "      <td>-6.016390e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>V25</td>\n",
       "      <td>V28</td>\n",
       "      <td>3.755328e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>V25</td>\n",
       "      <td>Amount</td>\n",
       "      <td>-4.783686e-02</td>\n",
       "      <td>6.441274e-144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>V25</td>\n",
       "      <td>Time</td>\n",
       "      <td>-2.330828e-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>V26</td>\n",
       "      <td>V27</td>\n",
       "      <td>-2.850613e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>V26</td>\n",
       "      <td>V28</td>\n",
       "      <td>-2.947794e-16</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>V26</td>\n",
       "      <td>Amount</td>\n",
       "      <td>-3.208037e-03</td>\n",
       "      <td>8.688928e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>V26</td>\n",
       "      <td>Time</td>\n",
       "      <td>-4.140710e-02</td>\n",
       "      <td>2.692365e-108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>V27</td>\n",
       "      <td>V28</td>\n",
       "      <td>2.321951e-17</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>V27</td>\n",
       "      <td>Amount</td>\n",
       "      <td>2.882546e-02</td>\n",
       "      <td>2.016347e-53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>461</th>\n",
       "      <td>V27</td>\n",
       "      <td>Time</td>\n",
       "      <td>-5.134591e-03</td>\n",
       "      <td>6.140194e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>V28</td>\n",
       "      <td>Amount</td>\n",
       "      <td>1.025822e-02</td>\n",
       "      <td>4.383670e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>463</th>\n",
       "      <td>V28</td>\n",
       "      <td>Time</td>\n",
       "      <td>-9.412688e-03</td>\n",
       "      <td>5.076786e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464</th>\n",
       "      <td>Amount</td>\n",
       "      <td>Time</td>\n",
       "      <td>-1.059637e-02</td>\n",
       "      <td>1.557251e-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>465 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    FEATURE_X FEATURE_Y      PERSON_R              P\n",
       "0       Class        V1 -1.013473e-01   0.000000e+00\n",
       "1       Class        V2  9.128865e-02   0.000000e+00\n",
       "2       Class        V3 -1.929608e-01   0.000000e+00\n",
       "3       Class        V4  1.334475e-01   0.000000e+00\n",
       "4       Class        V5 -9.497430e-02   0.000000e+00\n",
       "5       Class        V6 -4.364316e-02  4.213111e-120\n",
       "6       Class        V7 -1.872566e-01   0.000000e+00\n",
       "7       Class        V8  1.987512e-02   2.740673e-26\n",
       "8       Class        V9 -9.773269e-02   0.000000e+00\n",
       "9       Class       V10 -2.168829e-01   0.000000e+00\n",
       "10      Class       V11  1.548756e-01   0.000000e+00\n",
       "11      Class       V12 -2.605929e-01   0.000000e+00\n",
       "12      Class       V13 -4.569779e-03   1.473734e-02\n",
       "13      Class       V14 -3.025437e-01   0.000000e+00\n",
       "14      Class       V15 -4.223402e-03   2.420143e-02\n",
       "15      Class       V16 -1.965389e-01   0.000000e+00\n",
       "16      Class       V17 -3.264811e-01   0.000000e+00\n",
       "17      Class       V18 -1.114853e-01   0.000000e+00\n",
       "18      Class       V19  3.478301e-02   5.801517e-77\n",
       "19      Class       V20  2.009032e-02   7.964292e-27\n",
       "20      Class       V21  4.041338e-02  3.002269e-103\n",
       "21      Class       V22  8.053175e-04   6.673597e-01\n",
       "22      Class       V23 -2.685156e-03   1.518602e-01\n",
       "23      Class       V24 -7.220907e-03   1.163760e-04\n",
       "24      Class       V25  3.307706e-03   7.752501e-02\n",
       "25      Class       V26  4.455398e-03   1.741971e-02\n",
       "26      Class       V27  1.757973e-02   6.441920e-21\n",
       "27      Class       V28  9.536041e-03   3.595354e-07\n",
       "28      Class    Amount  5.631753e-03   2.651221e-03\n",
       "29      Class      Time -1.232257e-02   4.818269e-11\n",
       "..        ...       ...           ...            ...\n",
       "435       V22    Amount -6.480065e-02  1.326596e-262\n",
       "436       V22      Time  1.440591e-01   0.000000e+00\n",
       "437       V23       V24  6.721881e-17   1.000000e+00\n",
       "438       V23       V25 -7.216610e-16   1.000000e+00\n",
       "439       V23       V26  1.284235e-15   1.000000e+00\n",
       "440       V23       V27  4.382861e-16   1.000000e+00\n",
       "441       V23       V28  1.364554e-15   1.000000e+00\n",
       "442       V23    Amount -1.126326e-01   0.000000e+00\n",
       "443       V23      Time  5.114236e-02  3.134910e-164\n",
       "444       V24       V25  1.241447e-15   1.000000e+00\n",
       "445       V24       V26  1.875868e-16   1.000000e+00\n",
       "446       V24       V27 -3.054513e-16   1.000000e+00\n",
       "447       V24       V28 -2.789797e-16   1.000000e+00\n",
       "448       V24    Amount  5.146217e-03   6.025251e-03\n",
       "449       V24      Time -1.618187e-02   5.803460e-18\n",
       "450       V25       V26  2.435139e-15   1.000000e+00\n",
       "451       V25       V27 -6.016390e-16   1.000000e+00\n",
       "452       V25       V28  3.755328e-16   1.000000e+00\n",
       "453       V25    Amount -4.783686e-02  6.441274e-144\n",
       "454       V25      Time -2.330828e-01   0.000000e+00\n",
       "455       V26       V27 -2.850613e-16   1.000000e+00\n",
       "456       V26       V28 -2.947794e-16   1.000000e+00\n",
       "457       V26    Amount -3.208037e-03   8.688928e-02\n",
       "458       V26      Time -4.140710e-02  2.692365e-108\n",
       "459       V27       V28  2.321951e-17   1.000000e+00\n",
       "460       V27    Amount  2.882546e-02   2.016347e-53\n",
       "461       V27      Time -5.134591e-03   6.140194e-03\n",
       "462       V28    Amount  1.025822e-02   4.383670e-08\n",
       "463       V28      Time -9.412688e-03   5.076786e-07\n",
       "464    Amount      Time -1.059637e-02   1.557251e-08\n",
       "\n",
       "[465 rows x 4 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_stats.to_csv(path + '/feature_stats.csv', index = None, sep = '\\t')\n",
    "del feature_stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 各特征与类别标签间的相关性可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 相关系数显示\n",
    "corr = data[features].corr()\n",
    "feature_nums =  len(features)\n",
    "cols =  corr.nlargest(feature_nums, 'Class')['Class'].index\n",
    "cm = np.corrcoef(data[cols].values.T)\n",
    "\n",
    "f, ax = plt.subplots(figsize = (20, 20))\n",
    "sns.set(font_scale = 2)\n",
    "hm = sns.heatmap(cm,\n",
    "                 cbar = True,\n",
    "                 annot = True,\n",
    "                 square = True,\n",
    "                 fmt = '.2f',\n",
    "                 annot_kws = {'size' : 12},\n",
    "                 yticklabels = cols.values,\n",
    "                 xticklabels = cols.values\n",
    "                )\n",
    "\n",
    "# 设置刻度字体大小  \n",
    "plt.xticks(fontsize = 16) \n",
    "plt.yticks(fontsize = 16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    }
   ],
   "source": [
    "# 可视化变量间的相关性\n",
    "fig = plt.figure(figsize = (12, 8))\n",
    "for i in range(1, len(features)):\n",
    "    data_sub = pd.concat([data['Class'], data[features[i]]], axis = 1)\n",
    "    sns.set_palette('muted')\n",
    "    sns.jointplot(x = 'Class',\n",
    "                  y = features[i],\n",
    "                  data = data_sub,\n",
    "                  kind = 'reg',\n",
    "                  color = 'r',\n",
    "                  space = 0.5,\n",
    "                  ratio = 5)\n",
    "    plt.title('Class' + ' - ' + features[i], fontsize = 16)\n",
    "    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签  \n",
    "    plt.rcParams['axes.unicode_minus'] = False   # 用来正常显示负号"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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